With conventional techniques, a dedicated frequency band is allocated to each of multiple wireless communication systems to avoid interference between them and maintain the signal quality. In recent years and continuing, however, studies and research have been conducted of sharing the same frequency band among multiple systems for the purpose of more efficient use of frequency resources. It is necessary for such a system to prevent interference from the other coexisting networks and maintain the signal quality of desired signals at each of the networks.
FIG. 1 is a schematic diagram illustrating signal transmission between transmitters and a receiver used in a spectrum sharing environment. In the figure, two wireless communication systems coexist in and share the same spectrum band. User 1 and user 2 belong to different communication systems. The signal transmitted from user 2 is an interfering signal for user 1. With a conventional wireless communication system, the transmission-side filter 1 and the receiving-side filter 3 are paired with each other, and the transmission characteristics of the filters are fixed so as to achieve appropriate band limitation.
FIG. 2 through FIG. 5 illustrate how the signals are processed at the transmitters and the receiver in the conventional system. Signals A1, A2, . . . , H, and I illustrated in FIG. 2 through FIG. 5 correspond to the signals indicated by the same symbols in FIG. 1.
FIG. 2A illustrates a modulated baseband signal (frequency spectrum) A1 of an impulse sequence generated for user 1, FIG. 2B illustrates a band-limited frequency spectrum B1 having passed through the root-raised cosine filter, and FIG. 2C illustrates frequency spectrum C1 of the RF signal to be transmitted for user 1. Carrier frequency f1 is used to transmit the desired signal for user 1. The signal is transmitted over a symbol period T1, with the Nyquist bandwidth of 1/T1. The Nyquist bandwidth of the desired signal that satisfies symbol rate 1/T1 is between negative ½T1 and positive ½T1.
FIG. 3A illustrates a modulated baseband signal (frequency spectrum) A2 of an impulse sequence generated for user 2, FIG. 2B illustrates a band-limited frequency spectrum 32 having passed through the root-raised cosine filter, and FIG. 2C illustrates frequency spectrum C2 of the RF signal to be transmitted for user 2. Carrier frequency f2 is used to transmit the desired signal for user 2. The signal is transmitted over a symbol period T2, with the Nyquist bandwidth of 1/T2. The Nyquist bandwidth of the desired signal that satisfies symbol rate 1/T2 is between negative ½T2 and positive ½T2.
FIG. 4A illustrates signal spectrum D received at the receiver of user 1, which spectrum contains (1) a desired signal component, (2) an undesired (interfering) signal component, and (3) a noise component. The combination of the components (1), (2), and (3) defines the total spectrum of the received signal. FIG. 4B illustrates a frequency-converted spectrum E obtained through frequency conversion from the RF frequency to the baseband frequency at the receiver of user 1. FIG. 4C illustrates a band-limited spectrum F having passed through the receiving filter 3 of the user 1 receiver.
FIG. 5A illustrates an ideally equalized desired signal output from the adaptive filter at the user 1 receiver. By performing symbol rate sampling on the equalized signal G, spectrum H appears on the frequency axis, as illustrated in FIG. 5B. Spectrum H is a repetition of spectrum G of FIG. 5A, appearing at the multiples of 1/T1. FIG. 5C illustrates output data (or restored transmission signal) I for user 1 obtained by combining individual spectra H.
One method for reducing interference from other systems is to transmit and receive communication parameters to and from other systems such that each system can prevent interference from other systems. This method, however, is not always available, and interfering signals from other systems cannot be sufficiently reduced when, for example, the communication parameters of other systems are unknown, the carrier frequency of the interference signal is dynamically changing (due to frequency hopping or other factors), or transmission of communication parameters itself is difficult between different systems.
The above-described conventional method for reducing interference from other systems employs maximum likelihood sequence estimation or linear equalization based on recursive processing. Such a method, however, requires each system to know information about parameters (such as modulation schemes, training symbols, or symbol rates) of other systems in advance. Accordingly, if parameters of other systems are unknown for some reason, this method cannot work efficiently.
Another method for removing interfering signals of other systems is to use a fractionally spaced equalizing (FSE) filter or a frequency shift (FRESH) filter. FIG. 6 is a schematic diagram of a FRESH filter, and FIG. 7 is a schematic diagram of an FSE filter. The FSE and the FRESH filters can be used as the adaptive filter shown in FIG. 1. As illustrated in FIG. 6, a FRESH filter includes parallel-connected FSE filters, the outputs of which filters are combined and subtracted from a training signal to produce an error signal. The filter coefficient of each of the FSE filters is adjusted so as to minimize the error signal. Each FSE filter has a series of delay elements for delaying the oversampled input signal, as illustrated in FIG. 7. The outputs of the delay elements are multiplied by the associated coefficients (or weighting factors) ci, respectively, and combined together. The weighing factors are called tap coefficients. Details of FRESH and FSE are described in, for example, W. A. Gardner, “Exploitation of spectral redundancy in cyclostationary signals”, IEEE Signal Processing Magazine, vol. 8, no. 2, pp. 14-36, April 1991, and W. A. Gardner, “Cyclic Wiener filtering: theory and method”, IEEE Trans. Commun., vol. 41, no. 1, pp. 151-163, January 1993.
With the above-described conventional techniques, the characteristics of transmission filter 1 and receive filter 3 shown in FIG. 1 are fixed by system design so as to define a paired matched filter, while dynamic compensation, such as compensation for channel fluctuation, is assigned solely to the adaptive filter. It is therefore of concern that interference removing ability is insufficient, depending on the interfering conditions. In particular, as the carrier frequency of the desired signal and that of the undesired signal become closer to each other with the parameters of the undesired signals unknown, prevention of interference becomes more difficult.
By the way, the characteristic of a pulse shaping filter (filter 1, 2 or 3 shown in FIG. 1) is defined by a pulse transmission period and a pulse width. The pulse transmission period (Ts) is in inverse proportion to the symbol rate (i.e., the Nyquist bandwidth) expressed as 1/Ts. The pulse width is inversely proportional to the bandwidth of the pulse shaping filter. As illustrate in FIG. 8, the bandwidth of a pulse shaping filter is defined as the Nyquist bandwidth and the excess bandwidth, and the Nyquist bandwidth is defined as symbol rate 1/Ts. The excess bandwidth is a subtraction of the Nyquist bandwidth from the bandwidth of the pulse shaping filter. The excess bandwidth is expressed as a percentage with respect to the Nyquist bandwidth. For example, if the bandwidth of the pulse shaping filter and the Nyquist bandwidth are 2.4/Ts and 1/Ts, respectively, the excess bandwidth is 140%, as illustrated at the left-hand side of FIG. 8. If the Nyquist bandwidth is 2/Ts, then the excess bandwidth is 20%, as illustrated at the right-hand side of FIG. 8. If the Nyquist bandwidth is broad, the data transmission amount can be increased. Accordingly, the excess bandwidth is fixed to be narrow in general; however, with a narrow excess bandwidth, the interference capability of the FRESH and the FSE filters for removing in-band interference is also small.
In addition, presence of the in-band interference signal in the desired signal bandwidth and the availability of adjacent channels of the desired signal change with time depending on the traffic, and therefore the interference removing ability of each system also changes depending on the traffic. It is accordingly of concern that the interference cannot be removed sufficiently and the throughput may be degraded rapidly, depending on the conditions.